Modeling the Structure and Evolution of Discussion Cascades

摘要

We analyze the structure and evolution of discussion cascades in four popular websites: Slashdot, Barrapunto, Me-neame and Wikipedia. Despite the big heterogeneities between these sites, a preferential attachment. (PA) model with bias to the root can capture the temporal evolution of the observed trees and many of their statistical properties, namely, probability distributions of the branching factors (degrees), subtree sizes and certain correlations. The parameters of the model are learned efficiently using a novel maximum likelihood estimation scheme for PA and provide a figurative interpretation about the communication habits and the resulting discussion cascades on the four different websites.